Triple
T5832647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peugeot Boxer |
E129387
|
entity |
| Predicate | grossVehicleWeightRange |
P20168
|
FINISHED |
| Object | approximately 3.0–4.0 tonnes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: approximately 3.0–4.0 tonnes | Statement: [Peugeot Boxer, grossVehicleWeightRange, approximately 3.0–4.0 tonnes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grossVehicleWeightRange Context triple: [Peugeot Boxer, grossVehicleWeightRange, approximately 3.0–4.0 tonnes]
-
A.
announcedGrossVehicleWeightRating
Indicates that an entity has a specified gross vehicle weight rating that has been formally announced or declared.
-
B.
associatedVehicleWeightClass
chosen
Indicates the weight classification category that is linked or assigned to a particular vehicle.
-
C.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
-
D.
towingCapability
Indicates the maximum load or object weight that one entity is able to pull or tow.
-
E.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.